Noah Healy’s Introduction and Career Journey
Ryan: I’m your host, Ryan Davies, and I’m hosting today’s discussion on changing traditional methods through algorithmic marketplace design with Noah Healy. Noah. Thanks for joining us.
Noah: Thanks for having me here, Ryan.
Ryan: Excellent a little bit about Noah. So early in his career, Noah used computational mathematics and software development capabilities to develop automation that boosted internal productivity, drove client efficiencies, and improved regulatory compliance. Most recently, Noah founded Coordisc and developed a CDM, a technology product that has the potential to completely reorder the global financial system, which is just that sentence alone gets me all excited on the inside.
CDM Technology and Its Revolutionary Potential
Ryan: CDM creates a better commodity exchange market by ensuring fair prices, improving price discovery, reducing transaction costs, and eliminating the need for hedging. Only a portion of trade flow is needed to get this product off the ground and enhance its effectiveness. One of the significant benefits of CDM is its rapid scalability. It has the potential to change the way we conduct trading and business fundamentally. Let’s delve into what CDM does and its massive advantages.
Noah: So CDM is a mechanism for price discovery. it needs to embed itself into a marketplace, it needs the buyers and sellers, and so on. What it does is it changes the structure of the competition between producers and consumers by adding in the price makers. So Wall Street or Chicago or these people, the intermediaries actually have a vital role within the system of finding and providing information about where prices live and where they’re headed. Unfortunately, the existing market rewards them, not for being right, but simply for finding somebody who’s more wrong than they are in trading with them. The marketplace essentially throws everybody people who farm or mine or have a factory and just need a product to move and can’t afford to track all the information in the world with people who can’t afford to track all the information in the world as well as day traders who have widely varying levels of interest and knowledge and so on and kind of toss them all into, a single mosh pit. And that means that the dominating strategy over the last several decades with computerization has become finding the most ignorant person in the mosh pit with you and just destroying them personally. And on average, the most ignorant people in the marketplace are the people who have to use it to make their businesses operate. And so what we’ve seen in the last several decades is 10 X improvements in productivity in agriculture and manufacturing, but profitability has not moved very much because the markets have essentially been able to keep all of that productivity gain for themselves. And that’s not because they’re just so smart. It’s because computer technology has given them such an edge in speed and awareness that it’s not possible to compete against them.
Noah: So what I do is I take that aspect of the market, that price maker aspect, and I segregate it into its own marketplace. And so they can’t find, the kid that just stumbled in and needs a job and exploit them as hard as possible. They have to, fight on even terms with other people that have stepped onto the field to figure out what prices are gonna turn out to be. And then the collective knowledge and wisdom of all the price makers get turned over to the price takers into a flat marketplace that still trades because there are producers and consumers, they need to connect to each other, and the commissions that they pay are considerably cheaper than the losses that they currently incur from whatever the worst possible deal they’re willing to accept is pays out the entire system. Now, this might sound like a raw deal. But because of the way that I’ve structured that first marketplace for the price makers in my market, they actually have less downside risk, and they can never lose more than they’re willing to wager in the first place. And existing markets can’t control their rates of return. And so average rates of return in the various marketplaces are roughly equivalent, somewhere in the sort of 10 to 15% range is, is doing pretty well in my markets, stably improving. That is possible. So somebody like Warren Buffett is famous for achieving 30 ish percent returns. Over the course of decades, a CDM can produce a market in which average rates of return could be at 100% or 1000% or any other parameter that market operators decided to set as an incentive to get people to come in and provide their information by simply lowering the cost of participation, and it’s all limited in information. So you can’t, just spuriously drop a billion dollars and say, OK, give me my money later. You have to have new, fresh information that is moving the marketplace in order to make an investment.
Ryan: This gives you kind of a level ground here. This sort of takes away your ability of the ones who again kind of control a little bit more of the wealth in terms of they’ve got their supercomputers that are running, they’ve got the big hedge funds that are working that they can, sort of game the market prices a bit and, and bring it down to sort of that level. Is that, how I understand it like that? That’s kind of one of the biggest advantages like you said.
Noah: Yeah. absolutely this has been a very serious issue around the world for something like five decades. Now, we’ve seen a divergence between worker productivity and, sort of median incomes or, sort of normal lifestyles. And that’s because communication isn’t something everybody is equally good at and computers hypercharging communication have given the communication capable larger and larger shares of our economy. But we all still need to eat, we all still need to wear clothing, we all still need, you know, this stuff. And so the whole board is tilted well away from being productive, and what this does is it just re-reestablishes that and makes being productive profitable again.
Ryan: And it allows, I guess, one of the biggest, again, as you mentioned, access to information, access to data, being able to use that to your advantage. This kind of, again, brings that big data into that smaller size that everybody can finally access. How are you able to take advantage of that and bring that to people? I mean, it sounds almost impossible in my head how hard it is to collect big data, all this information, but to bring it down to this level and for people to be able to, to take advantage of it in this way, again, the great, equalizer, I guess, right, the field level,
Noah: Well, again, that’s actually what markets are for in the first place. Markets have been providing that function for centuries. And that’s where the idea of, say, the invisible hand comes from. That’s why our existing market models took off, and sort of caused the renaissance. The economy is a big, hard problem to solve. And part of the big hard problem is that we’re part of the problem, and every one of us comes equipped with a brain with its own interests. And so sort of no one of us can be as smart as all of us are. And so, the marketplace exists as a technology to distill all these opinions into a number. The price. My insight goes slightly further than that and says that yes, the price is very important, but what’s really important isn’t the price because prices aren’t fixed in time, but the way price evolves over time. So rather than having a market focused on finding the price. Then a microsecond later finding the price again, creating a market that’s structured to figure out how the price is going to evolve into the future. And so working on that sort of price line instead of a single point. And once you get that perspective going, then, a lot of things become much more clear, and the market’s interests very much stabilize because, whereas with things like massive market crashes, there’s a very high V price, that’s sort of too high, and people make money there if they’re on the right side of it. And then a few seconds later, there’s a, V price that’s way too low, and maybe the same people can make money by being on the right side of that as well. But the marketplace in general and the economy in general aren’t benefiting from the price being too high or too low. It would prefer that that particular, waterfall never happened. And so when you’re focused on figuring out what the timeline of prices is supposed to look like, then you can start, you can sort of look ahead and say, oh, ok, these prices are too high, and then they’re going to have to be too low. Let’s just even those out into where prices need to be to sort of make things smooth.
Challenges in Traditional Market Structures
Ryan: So you talked about there, you mentioned both the Renaissance, right? And that was the change, and I kind of feel like almost we’re at another, version of that right now where technology is catching up to it, or I guess not even catching up, it’s just exceeding where maybe the tradition in the markets have been. And things like that. But there are huge gaps that obviously exist when you’re trying to change a system that’s rooted in hundreds and hundreds of years. Well, that’s how we’ve always done it. So, how have you encountered that and, been able to, kind of bridge some of those gaps, and what gaps have you, identified maybe still exist or you see are gonna be crumbling down now as you continue forward?
Noah: Well, some of this, I actually explore, I have a podcast with the former CTO of Reddit Marty Weiner, called the Fourth Age. And, it directly addresses that issue. That’s the fourth age is in sort of a next renaissance is what we hope these technologies, will bring forth. But the same advantages in communication that are causing these issues in the marketplace are also things that we can take advantage of. So I’ve been able to build a global network through Zoom and social media to find potential customers. And the people that I’m currently working with, to provide, the technology for them to incorporate into their marketplaces are scattered all over the planet. And I’ve never, well, I’ve been in the room with one of them, but you know, it was a special circumstance basically. they all live in different countries than me. The closest is, I don’t know, 3, 4000 miles away. So, the, things that are breaking the systems that we have are also providing these new capacities, and so you need to, sort of work by analogy and, work with the grain, which is what I’m doing so far.
Ryan: So let’s, rewind a little bit on your journey here a bit. I mean, you were if I, remember reading correctly here, right? The last person who was admitted to the University of Virginia’s Nuclear Engineering program. And you’ve been doing this for a long time. Tell me where this came from in terms of the ideation stage, how, you decided to, come up with this less low-risk kind of idea for commodity markets and, and bring this from ideation to product.
Noah: Well, I’m a recreational mathematician, and the part of math that I’m interested in is computational mathematics. And I was, in a position where the company I worked for, by policy had no career opportunities. And so I left, I had a fair amount of money in the bank, and I decided to sort of build my own sabbatical, if you will, and spent a few years thinking about these, computational math problems and something that’s relatively underappreciated I think is that in many ways, this is similar to mechanical, types of things, that these ideas are bringing ideas and imagination into the sorts of measurement that we associate with machines. So it’s, it’s like being an inventor in like the Ford, right days. But instead of playing around with bike chains in Greece, you can play around with your imagination. And the trick is you need to use computer programs to check essentially whether or not what you’re doing actually compiles and runs and, has the efficiencies that, it looks like it does. And so that’s what I was thinking, and I was working out these ideas of how collective intelligence can work. And how collaborative intelligence can function with people and machines because I could see that we were heading towards realms or, in many cases, already places where computer hardware would have information that was relevant. But we don’t communicate very well with computer hardware. And so, finding ways to make that kind of system efficient and effective struck me as, an important place to work. And that’s where markets and, game theory as an approach came to me. once I’d come up with a straightforward version, I then had this intuitive insight that a recursive version might be capable of operating as a marketplace.
Noah: And frankly, just as, a matter of personal interest. I had absorbed with everyone else in a sort of econ intro that marketplaces were perfect. And so I had no expectation that anything I was working on would demonstrate any kind of improvement. But after several months of, working out the details, writing the code, and finding out what happens as a result of that, I was quite shocked to learn that I had just re-innovated marketplaces in a way that was of significant upgrade. And so then I kind of retooled my life, into this pursuit, figuring out how to, communicate this very abstruse mathematical idea into a very practical computer program into an actual system that people could understand and decide that they wanted to participate in.
Ryan: It’s quite, the journey to be able to to undertake that. And with that, who are the ideal partners that can really realize the potential that CDM provides because I can imagine there it goes everywhere, like you said, across the board for people that can really use and take advantage, of what it can do.
Noah: Yeah, absolutely. So market operators are number one because they’re essentially already in a position of handling money and having a customer base and so on. Another interesting possibility would be activist industry associations. So if lamb ranchers or, steel manufacturers or something like that, wanted to secure their supply chains and, in a broader sense, across multiple industries, establishing a more effective market is the best way to do that. So, they would also be good. And then enterprising people with enough wherewithal and Moxie to get through the regulatory thicket of whatever their local government concerns are.
I’m willing to talk to you, too, because so far, those are the people that I’ve managed to corral, into having some interests and shifting gears.
The Role of AI in Society and Economy
Ryan: You mentioned before that you have your own podcast, the Fourth Age as well. So I know you mentioned that it talks about AI’s impact on society and the economy, and I would assume into politics, and it kind of expands beyond that. But, give our listeners a little taste of that as well. So we can we can share some of that. some of our listeners there with you.
Noah: Absolutely. Yeah. It’s called the Fourth Age, and the subtitle is the AI Revolution. Marty Weiner, as I said, is the former CTO of Reddit. He was with Pinterest at the founding, and basically, the two of us met on an AI ethics panel he had put together he was looking for more AI theorists, and mutual friends put us together, and we did the panel. It was a huge hit, and we decided, let’s launch a podcast and see if we could keep this going. And the fourth age is based on an idea I’ve had for a while. that specific name that there have been three knuckle innovations inventions in human history. The plow, the steam engine, the watt steam engine, and the computer. What makes these things special and important is that they change humans, energy, and physical relationships with the environment in a serious way. Each one of them is accompanied by changes in the political, religious, cultural, and economic structure of the societies that manage to utilize them. And so, since computers make controlling systems radically less expensive than it’s ever been before, you don’t have to use a human brain anymore. You can use a few pennies of silicon. Now, we should expect all our political, cultural, economic, and religious systems to change and any aspect of any of those things anybody likes. And presumably, there are lots of aspects of lots of those things that people like. we need to do the work to figure out how to incorporate those things that we like into systems that have futures. Because if you plan that things are going to be like this for, a while, but we’re also going to have smartphones, then your plan isn’t reasonable or sane,
Overcoming Resistance to Technological Change
Ryan: we mentioned it before. It is that gap that exists, between them. Well, I’m a traditionalist. This is how it’s always done, or if I’m not comfortable, therefore I’m going to stick, with it. And some of it goes back only a decade or two. And some of it, you mentioned, even into political and religious areas, you’re going back thousands of years or more at this stage now. So it’s, incredibly challenging. How do you personally find yourself dealing with that? When you run into people that are just so resistant to it? Is it, just sort of like, hey, look, I’ve got the proof here? There’s, a level of acceptance, or is it some real head bay against your wall moments where you’re like, how are you not getting this? It’s kind of uncomfortable.
Noah: It’s a big lift. And I’m a math guy first and foremost. So, like the proof right here, that’s the thing that I keep coming back to is that is I’ve got the proof right here. The book-proof version for Coordinate Discovery Markets is that it’s extracting the same information from the same population of people by using better incentives. So if you don’t think CDM works, then you don’t think the existing markets work either, but for the people that run the existing markets, that doesn’t really work for them, they’re like, nope, I’m doing this, and I’m making money. You said blah, blah stuff, and I don’t care. So you have a lot of fruitless conversations. and you try things out, and everything that you say that gets a glimmer, you try that out on some other people and see what glimmers you get, and you hone the message, and you have as many conversations as you can and just, incremental. I can’t know whether or not I’ll succeed, but I can know whether or not I’ll try. And so I’m working on the things that I can control. but opposition comes up all over the place and in very unexpected ways. I’ve been working on the patent for something like eight years now, and the patent office is pretty much literally twisting itself into knots to not grant that patent. So, they accepted it the first time four years ago, and then they ignored their own acceptance and came up with a counterargument that was mathematically invalid. And when that was pointed out to them, they accepted it about two years ago. And then, three weeks later, they withdrew the second acceptance because they were told to do so by people who were not allowed to talk to me and my attorneys about it, and then they posted a reason that basically says that if this patent is extended, I will have control of all economic activity. And so they’re not going to do it. And they said, well, and by the way, I’m sorry, this doesn’t make any sense. We know this doesn’t make any sense. We can’t make any sense of the people that told us to do this. So we can’t give you anything that makes sense. So we won’t take this back because it doesn’t make sense. So now we’re appealing to the patent board, and, that hearing has been scheduled for the summer of 2025. So we’ll see, what a judge thinks in a year and a half.
Ryan: My goodness.
Noah: And, yeah, there’s a lot of stone walls and, a lot of delays, and there’s just not much to do, but the patent office has acknowledged that there’s zero prior art. They had five different things they tried, and they agreed that none of them was anything like my idea. And they’ve also agreed that this is a considerable advance in the state of the art. And so, people that look at it and think about it, can figure out that it’s new and it’s better. It’s just down to whether or not people who are in a position to start marketplaces would like to do better and have a future or whether they’re gonna go down with the ship.
Ryan; Why do I feel like this is the start of a movie that we’re going to see is released in about 2035 of this journey that happened and the suppression and then turns into this revolutionary thing. I want to follow this journey. Our listeners are going to wanna follow your journey here. We have a year and a half to follow and tell that it happens. How do people follow? Get connected with you? Where do we find the podcast? Give us the rundown. Noah.
Noah, absolutely. So for me, you can reach out to me directly at noahphealy@yahoo.com or connect with me on LinkedIn. I’m Noah Healy there. You can learn more about Coordisc. There’s a website https://coordisc.com/faq/ And there’s information there. The podcast is called the Fourth Age. It should be up on Spotify. We’re coming to YouTube. We’re on Google, but Google is like merging. So we’ll see Apple podcasts also. We’re on substack and the fourthage.com That’s for the number four. So fourthage.com actually redirects to our substack. So, that should be easier to find as more and more people come and listen to us.
Ryan: Love it. This is great. So who’s going to play you in the movie? I guess that’s our next question.
Noah: So we’ll have to figure that we’re going to have to figure that question. Well, there’s a real question of whether I’m hoping that this comes out, and then, it’s that kind of situation where it all wins, and then I get to be the executive producer, and I get to pick who I want to be. But the other one is that it’s one of those ones like Tucker, the man in his dream. And it’s a triumph, and it was a revolution, but it’s not, I’m not the guy, and then, the, the filmmaker, it doesn’t come out in 2035, it comes out in like, you know, 2085 and they’re like, isn’t it great that we have this technology that this guy showed us? But everybody ignored him. So we’ll see which way it winds up having.
Ryan: this is amazing. It was a great, great podcast episode. I hope that we get to continue and do this again. I think there are so many things that we could talk about, and, for all of our listeners again, Coordisc, go check out the fourth Age podcast. Definitely give it a listen. I know I’m going to be subscribing to it and giving it a listen as well. So, with that, I think we bring this to a close for today. And again, Noah, hopefully, we can have you back and continue our discussion. So, thank you so much for being here.
Noah: Thanks for having me here. This was a lot of fun.
Ryan: Absolutely. So I want to thank you again, take a minute. Thank Noah for this amazing podcast, Noah Healy, with changing traditional methods through algorithmic marketplace design. I think we stretched it even further beyond those barriers. And we got a lot more that we could talk about just from some of the subtopics we talked about today. And I want to thank our listeners. We can’t do what we do without you. So until we meet again with another amazing TBR episode, I’m your host, Ryan Davies. Take care out there. Thanks, everybody.